EFFECT OF VARYING ENERGY-PROTIEN DIETS AND PGF2α ADMINISTRATION ON REPRODUCTIVE AND BIOMETRIC CHARACTERISTICS OF TWO BREEDS OF SHEEP
Keywords:
Low energy diets, medium energy diets, High energy diet, Yankasa, Uda Breeds Reproductive, Biometrics CharacteristicsAbstract
A study was conducted to determine the effect of feeding three different energy diets on reproductive parameters and biometric characteristics of two breeds of sheep in the Sudan savannah zone of Nigeria. Eighteen (18) mature non-pregnant sheep (9 Uda and 9 Yankasa) with an average live weight of 34.33±1.25 kg was fed diets containing Low, Medium and High energy levels. The diets comprised of 45%, 55% and 65% energy designated as T1, T2, and T3, respectively. The animals were allotted to the three dietary treatments in a 2×3 factorial arrangement in a Completely Randomized Design, replicated three times. The experiment lasted for 36 weeks, and experimental diets were fed at 10% of the experimental animal’s body weight. A significant (P<0.05) difference was observed in T3 (HED), which plays a vital role in controlling the estrous and gestation period in Yankasa breeds while in Uda breeds T1 (LED) influences the estrous and gestation period. Similarly, a significant (P<0.05) differences were observed in Yankasa breeds fed (HED) on Pregnancy rate, lambing rate, twinning rate, no abortion, and still birth records. Also, the Yankasa breed scores 100% rate in all three energy diets (LED, MED and HED) but Uda scores 33.33 and 33.33% Pregnancy rate, lambing rate and abortion rate. Significant (P<0.05) differences were observed on body and neck length in both breeds (MED) for body length (76.73 cm) and neck length (33.06 cm) neck length in the Yankasa while Uda breeds T1 (LED,) body length (81.31 cm) and neck length (32.76 cm) was recorded. Data generated were coded and then subjected to analysis of variance (ANOVA) using the General Lineal Model (GLM) of Statistical Analysis System (2009). Where significant differences between the means were observed, Fisher's least significant difference (LSD) was used to separate them at 5% level of probability (P<0.05).
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